EMA Research Blog: Navigating IT and Security Horizons

A year ago, EMA did some rather eye-opening research about what it takes to deliver business services over a mix of public and private, and non-cloud infrastructures. The research—dubbed “Ecosystem Cloud”—showed that an overwhelming 94% of the respondents felt that monitoring “inside” public cloud infrastructures was important—and 63% felt it was “very important” or “critical.” [...]

The term, “workload automation,” often conjures images of an army of robots zipping around an enterprise performing arduous tasks while the IT manager sits comfortably in a lounge chair at the back of the data center sipping a Mai Tai. Well, it’s not quite that Jetsonesque just yet – we’ll have to wait a few years for the robots and Mai Tais – but there is a fundamental truth in how workload automation dramatically reduces management effort and improves IT performance. Put simply, workload automation (sometimes still referred to as “job scheduling”) aggregates the placement and execution of individual business processes (i.e. applications, data bases, web services, or any other jobs that would be hosted by an enterprise IT system) to the optimal location (e.g. a server, a cloud, or a virtual machine) at the appropriate time to maximize performance and minimize costs.

A core precept in cloud computing is that it must deliver the illusion of infinite scalability.  That is, it must fulfill the expectation that any and all workloads will continuously operate at peak performance regardless of the size and number of jobs being added.  In reality, however, private cloud deployments are finite with limited compute, storage, and network resources. It’s kind of like a room full of mirrors – it seems to go on forever, but stretch your hand out and you’ll hit a wall.  The trick to successfully maintaining the illusion of infinite scalability is to allow workloads to extend beyond the scope of a single private cloud into other clouds and, in particular, into public clouds. Adopting this hybrid cloud approach also introduces opportunities for significant cost reductions and increased workload flexibility.

Steve Smythe discusses how IT Operations is transformed by big data solutions in his latest blog, “Transformation of IT operations with big data solutions.” Is this a reality? The answer—agreed upon here—is almost certainly “yes.” However, it should be pointed out that “big data,” or “IT Operations Analytics,” or as EMA calls it, “Advanced Operational [...]

It’s fascinating how the meaning for just about every term relevant to service management can be a matter of debate—including IT Service Management itself (a discussion for another time).  However, what’s sparking this blog centers around the three other terms in the headline—“service desk,” “Operations” and “Analytics,” plus a fourth—“cognitive computing.” In reading Brian Jeffrey’s [...]

On April 23^rd, 2014 Dell announced its new Vulnerability Threat Monitoring and Prioritization service delivered through the SecureWorks Counter Threat Platform.  This managed service was created to expand the current Vulnerability Management offerings and increase customer value by creating the ability for customers to integrate their own vulnerability management systems.  With the additional context provided through Risk I/O, remediation and mitigation prioritization are done less in a bubble of the operational environment and more in context with the Internet threat universe.

What’s the issue with BYOD? Data Control… What’s the issue with Data Sharing? Data Control!

The emotions oscillate between high frustration and high jubilation as I observe cyber-attack teams’ hacking activities against an unnamed financial institution…

As promised in my previous post on “Software Defined Storage – Why Customers Should Care”, I want to follow-up with a brief overview of the competitive landscape.